Summer Institutes in Computational Social Science launch online festival open to all
For the past few years in June, the Summer Institutes in Computational Social Science (SICSS) have seen students gather across the world at partner locations and in the designated primary location to begin a two-week program of collaboration, workshops, lectures, and participant-led research projects in computational social science (CSS). The strange times of COVID have somewhat altered these plans with some partner locations postponing until 2021 and some opting to move online. Whether virtual or postponed the fourth iteration of SICSS set a new record for partner locations—a total of 22 locations signed up to take part. Founders Matt Salganik and Chris Bail, allow participants to only attend once but as attendance has grown so have graduates returning to their institutions and setting up new partner locations.
'A great measure of our success is the community that SICSS creates'. Chris Bail and Matt Salganik on the Summer Institute in Computational Social Science
As the participants gear up for the 2019 Summer Institute in Computational Social Science (SICSS), starting June 16th at Princeton and the 11 alumni-led partner locations situated right across the globe, we caught up with the founders of the SICSS, Chris Bail and Matt Salganik to find out how it all got going, the move to a data intensive society and the benefits of learning data science skills to make the most of this new data.
Two weeks at the Summer Institute for Computational Social Science
In June, I attended the second iteration of the Summer Institute for Computational Social Science (SICSS), an intensive two-week program held at Duke that was intended to bring together researchers from across the social science and data science disciplines to learn and discuss topics in computational social science (CSS). Each day, the organizers Chris Bail and Matt Salganik taught mini-lectures on different CSS topics, we split into groups to work on activities together, and a speaker came in to present their research.
SICSS 2018 make all teaching and learning materials open-source
Teaching and learning resources from the 2018 Summer Institute for Computational Social Science have been made free to access online, allowing more people to explore in depth the field of computational social science.
Matthew Salganik: The Open Review of Bit by Bit
Open Review: better books higher sales, and increased access to knowledge